How quantitative is metabarcoding: A meta‐analytical approach

Metabarcoding has been used in a range of ecological applications such as taxonomic assignment, dietary analysis and the analysis of environmental DNA. However, after a decade of use in these applications there is little consensus on the extent to which proportions of reads generated corresponds to...

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Veröffentlicht in:Molecular ecology Jg. 28; H. 2; S. 420 - 430
Hauptverfasser: Lamb, Philip D., Hunter, Ewan, Pinnegar, John K., Creer, Simon, Davies, Richard G., Taylor, Martin I.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England Blackwell Publishing Ltd 01.01.2019
John Wiley and Sons Inc
Schlagworte:
biomass
Deoxyribonucleic acid
DNA
DNA barcoding
Ecological monitoring
Environmental DNA
high‐throughput sequencing
Meta-analysis
metabarcoding
Moderators
next‐generation sequencing
Sequences
Special Issue: Species Interactions, Ecological Networks and Community Dynamics
uncertainty
variance
meta-analysis
biomass
metabarcoding
next-generation sequencing
high-throughput sequencing
ISSN:0962-1083, 1365-294X, 1365-294X
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Zusammenfassung:Metabarcoding has been used in a range of ecological applications such as taxonomic assignment, dietary analysis and the analysis of environmental DNA. However, after a decade of use in these applications there is little consensus on the extent to which proportions of reads generated corresponds to the original proportions of species in a community. To quantify our current understanding, we conducted a structured review and meta‐analysis. The analysis suggests that a weak quantitative relationship may exist between the biomass and sequences produced (slope = 0.52 ± 0.34, p < 0.01), albeit with a large degree of uncertainty. None of the tested moderators, sequencing platform type, the number of species used in a trial or the source of DNA, were able to explain the variance. Our current understanding of the factors affecting the quantitative performance of metabarcoding is still limited: additional research is required before metabarcoding can be confidently utilized for quantitative applications. Until then, we advocate the inclusion of mock communities when metabarcoding as this facilitates direct assessment of the quantitative ability of any given study.
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ISSN:0962-1083
1365-294X
1365-294X
DOI:10.1111/mec.14920